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SDM
2012
SIAM
282views Data Mining» more  SDM 2012»
13 years 2 months ago
Citation Prediction in Heterogeneous Bibliographic Networks
To reveal information hiding in link space of bibliographical networks, link analysis has been studied from different perspectives in recent years. In this paper, we address a no...
Xiao Yu, Quanquan Gu, Mianwei Zhou, Jiawei Han
113
Voted
DAGM
2006
Springer
15 years 4 months ago
On-Line, Incremental Learning of a Robust Active Shape Model
Abstract. Active Shape Models are commonly used to recognize and locate different aspects of known rigid objects. However, they require an off-line learning stage, such that the ex...
Michael Fussenegger, Peter M. Roth, Horst Bischof,...
104
Voted
ML
2008
ACM
15 years 12 days ago
Inductive process modeling
In this paper, we pose a novel research problem for machine learning that involves constructing a process model from continuous data. We claim that casting learned knowledge in ter...
Will Bridewell, Pat Langley, Ljupco Todorovski, Sa...
MLDM
2005
Springer
15 years 6 months ago
Statistical Supports for Frequent Itemsets on Data Streams
Abstract. A statistical technique is developed for estimating the support of itemsets on data streams, regardless of the size of the data stored. This technique, which is computati...
Pierre-Alain Laur, Jean-Emile Symphor, Richard Noc...
BMCBI
2007
215views more  BMCBI 2007»
15 years 14 days ago
Learning causal networks from systems biology time course data: an effective model selection procedure for the vector autoregres
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
Rainer Opgen-Rhein, Korbinian Strimmer